1. Field of the Invention
The present invention relates generally to position, movement and gesture detection and, more specifically, to proximity-based position, movement and gesture detection utilizing hierarchical capacitive sensing.
2. Background of the Related Art
The Background of the Related Art and the Detailed Description of Preferred Embodiments below cite numerous technical references, which are listed in the Appendix below. The numbers shown in brackets (“[ ]”) refer to specific references listed in the Appendix. For example, “[1]” refers to reference “1” in the Appendix below. All of the references listed in the Appendix below are incorporated by reference herein in their entirety.
Home automation and environmental control is a key feature of smart homes. While systems for home automation and control exist, there are few systems that interact with individuals suffering from paralysis, paresis, weakness and limited range of motion that are common sequels resulting from severe injuries such as stroke, brain injury, spinal cord injury and many chronic (guillian barre syndrome) and degenerative (amyotrophic lateral sclerosis) conditions.
Indeed, an estimated 1.5 million individuals in the United States are hospitalized each year because of strokes, brain injuries and spinal cord injuries. Severe impairment such as paralysis, paresis, weakness and limited range of motion are common sequels resulting from these injuries requiring extensive rehabilitation. Changes in healthcare reimbursement over the past decade have resulted in shorter lengths of stay at hospitals and limitations on the amount of therapy that patients can receive post acute care. These changes present medical rehabilitation practitioners with a challenge to do more for patients with less time and resources.
It is imperative that practitioners implement assistive technologies efficiently and effectively to help patients maximize independence as early in the rehabilitation process as possible and provide methods to augment and supplement direct care that can be utilized over time to support recovery. This is particularly true for patient conditions where physical recovery can be a slow process over many years.
While assistive technology options currently exist to support access to communication and environmental control [1, 2], challenges remain that pose a barrier to early and efficient use of assistive technology in medical and settings. Current gesture recognition systems do not adapt to changes in body position and environmental noise. There is need for motion and gesture sensing solution that can: (1) reliably capture gestures regardless of the type of user, type of motion being captured and usage context; (2) that requires minimal set-up and maintenance; (3) causes minimal fatigue; and (4) is less intrusive than current solutions.